Adversarial Machine Learning: A Blow to the Transportation Sharing Economy

研究成果: 著書/レポートタイプへの貢献

抜粋

Adversarial machine learning has indicated that perturbations to a picture may disable a deep neural network from correctly qualifying the content of a picture. The progressing research has even revealed that the perturbations do not necessarily have to be large in size. This research has been transplanted to traffic signs. The test results were disastrous. For example, a perturbated stop sign was recognized as a speeding sign. Because visualization technology is not able to overcome this problem yet, the question arises who should be liable for accidents caused by this technology. Manufacturers are being pointed at and for that reason it has been claimed that the commercialization of autonomous vehicles may stall. Without autonomous vehicles, the sharing economy may not fully develop either. This chapter shows that there are alternatives for the unpredictable financial burden on the car manufacturers for accidents with autonomous cars. This chapter refers to operator liability, but argues that for reasons of fairness, this is not a viable choice. A more viable choice is a no-fault liability on the manufacturer, as this kind of scheme forces the car manufacturer to be careful but keeps the financial risk predicable. Another option is to be found outside law. Engineers could build infrastructure enabling automation. Such infrastructure may overcome the problems of the visualization technology, but could potentially create a complex web of product and service providers. Legislators should prevent that the victims of an accident, if it were still to occur, would face years in court with the various actors of this complex web in order to receive compensation.

元の言語英語
ホスト出版物のタイトルPerspectives in Law, Business and Innovation
出版者Springer
ページ179-208
ページ数30
DOI
出版物ステータス出版済み - 1 1 2020

出版物シリーズ

名前Perspectives in Law, Business and Innovation
ISSN(印刷物)2520-1875
ISSN(電子版)2520-1883

    フィンガープリント

All Science Journal Classification (ASJC) codes

  • Law
  • Management of Technology and Innovation

これを引用

Van Uytsel, S., & Vargas, D. V. (2020). Adversarial Machine Learning: A Blow to the Transportation Sharing Economy. : Perspectives in Law, Business and Innovation (pp. 179-208). (Perspectives in Law, Business and Innovation). Springer. https://doi.org/10.1007/978-981-15-1350-3_11